Dataset Information

Plasma proteome in multiple sclerosis disease progression.

ABSTRACT: BACKGROUND:The pathophysiology of multiple sclerosis disease progression remains undetermined. The aim of this study was to identify differences in plasma proteome during different stages of MS disease progression. METHODS:We used a multiplex aptamer proteomics platform (Somalogic) for sensitive detection of 1129 proteins in plasma. MS patients were selected and categorized based on baseline and a 4-year follow-up EDSS (delta EDSS) scores; relapse-onset (RO) slow progression (n = 31), RO with rapid progression (n = 29), primary progressive (n = 30), and healthy controls (n = 20). The relation of baseline plasma protein levels with delta EDSS and different MRI progression parameters were assessed using linear regression models. RESULTS:Regression analyses of plasma proteins with delta EDSS showed six significant associations. Strong associations were found for the proteins LGLAS8 (P = 7.64 × 10-5 , q = 0.06), CCL3 (P = 0.0001, q = 0.06), and RGMA (P = 0.0005, q = 0.09). In addition, associations of plasma proteins were found with percentage brain volume for C3 (P = 2,08 × 10-9 , q = 1,70 × 10-6 ), FGF9 (P = 3,42 × 10-9 , q = 1,70 × 10-6 ), and EHMT2 (P = 0.0007, q = 0.01). Most of the significant markers were associated with cell-cell and cell-extracellular matrix adhesion, immune system communication, immune system activation, and complement pathways. CONCLUSIONS:Our results revealed eight novel biomarkers related to clinical and radiological progression in MS. These results indicate that changes in immune system, complement pathway and ECM remodeling proteins contribute to MS progression and may therefore be further explored for use in prognosis of MS.

SUBMITTER: Malekzadeh A

PROVIDER: S-EPMC7651845 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Plasma proteome in multiple sclerosis disease progression.

Malekzadeh Arjan A Leurs Cyra C van Wieringen Wessel W Steenwijk Martijn D MD Schoonheim Menno M MM Amann Michael M Naegelin Yvonne Y Kuhle Jens J Killestein Joep J Teunissen Charlotte E CE

Annals of clinical and translational neurology 20190731 9

<h4>Background</h4>The pathophysiology of multiple sclerosis disease progression remains undetermined. The aim of this study was to identify differences in plasma proteome during different stages of MS disease progression.<h4>Methods</h4>We used a multiplex aptamer proteomics platform (Somalogic) for sensitive detection of 1129 proteins in plasma. MS patients were selected and categorized based on baseline and a 4-year follow-up EDSS (delta EDSS) scores; relapse-onset (RO) slow progression (n = ...[more]

PMID: 31364818

Similar Datasets

Project description:The negative impact of smoking in multiple sclerosis is well established; however, there is much less evidence as to whether smoking cessation is beneficial to progression in multiple sclerosis. Adults with multiple sclerosis registered on the United Kingdom Multiple Sclerosis Register (2011-20) formed this retrospective and prospective cohort study. Primary outcomes were changes in three patient-reported outcomes: normalized Multiple Sclerosis Physical Impact Scale (MSIS-29-Phys), normalized Multiple Sclerosis Walking Scale (MSWS-12) and the Hospital Anxiety and Depression Scale (HADS). Time to event outcomes were clinically significant increases in the patient-reported outcomes. The study included 7983 participants; 4130 (51.7%) of these had ever smoked, of whom 1315 (16.5%) were current smokers and 2815/4130 (68.2%) were former smokers. For all patient-reported outcomes, current smokers at the time of completing their first questionnaire had higher patient-reported outcomes scores indicating higher disability compared to those who had never smoked (∼10 points difference in MSIS-29-Phys and MSWS-12; 1.5-1.8 points for HADS-Anxiety and HADS-Depression). There was no improvement in patient-reported outcomes scores with increasing time since quitting in former smokers. Nine hundred and twenty-three participants formed the prospective parallel group, which demonstrated that MSIS-29-Phys [median (IQR) 5.03 (3.71, 6.34)], MSWS-12 [median (IQR) 5.28 (3.62, 6.94)] and HADS-Depression [median (IQR) 0.71 (0.47, 0.96)] scores worsened over a period of 4 years, whereas HADS-Anxiety remained stable. Smoking status was significant at Year 4; current smokers had higher MSIS-29-Phys and HADS-Anxiety scores [median (IQR) 3.05 (0.22, 5.88) and 1.14 (0.52, 1.76), respectively] while former smokers had a lower MSIS-29-Phys score of -2.91 (-5.03, -0.79). A total of 4642 participants comprised the time to event analysis. Still smoking was associated with a shorter time to worsening event in all patient-reported outcomes (MSIS-29-Phys: n = 4436, P = 0.0013; MSWS-12: n = 3902, P = 0.0061; HADS-Anxiety: n = 4511, P = 0.0017; HADS-Depression: n = 4511, P < 0.0001). Worsening in motor disability (MSIS-29-Phys and MSWS-12) was independent of baseline HADS-Anxiety and HADS-Depression scores. There was no statistically significant difference in the rate of worsening between never and former smokers. When smokers quit, there is a slowing in the rate of motor disability deterioration so that it matches the rate of motor decline in those who have never smoked. This suggests that smoking cessation is beneficial for people with multiple sclerosis.

Project description:BACKGROUND:Defining the transition from relapsing-remitting multiple sclerosis (RRMS) to secondary progressive multiple sclerosis (SPMS) can be challenging and delayed. A digital tool (MSProDiscuss) was developed to facilitate physician-patient discussion in evaluating early, subtle signs of multiple sclerosis (MS) disease progression representing this transition. OBJECTIVE:This study aimed to determine cut-off values and corresponding sensitivity and specificity for predefined scoring algorithms, with or without including Expanded Disability Status Scale (EDSS) scores, to differentiate between RRMS and SPMS patients and to evaluate psychometric properties. METHODS:Experienced neurologists completed the tool for patients with confirmed RRMS or SPMS and those suspected to be transitioning to SPMS. In addition to age and EDSS score, each patient's current disease status (disease activity, symptoms, and its impacts on daily life) was collected while completing the draft tool. Receiver operating characteristic (ROC) curves determined optimal cut-off values (sensitivity and specificity) for the classification of RRMS and SPMS. RESULTS:Twenty neurologists completed the draft tool for 198 patients. Mean scores for patients with RRMS (n=89), transitioning to SPMS (n=47), and SPMS (n=62) were 38.1 (SD 12.5), 55.2 (SD 11.1), and 69.6 (SD 12.0), respectively (P<.001, each between-groups comparison). Area under the ROC curve (AUC) including and excluding EDSS were for RRMS (including) AUC 0.91, 95% CI 0.87-0.95, RRMS (excluding) AUC 0.88, 95% CI 0.84-0.93, SPMS (including) AUC 0.91, 95% CI 0.86-0.95, and SPMS (excluding) AUC 0.86, 95% CI 0.81-0.91. In the algorithm with EDSS, the optimal cut-off values were ?51.6 for RRMS patients (sensitivity=0.83; specificity=0.82) and ?58.9 for SPMS patients (sensitivity=0.82; specificity=0.84). The optimal cut-offs without EDSS were ?46.3 and ?57.8 and resulted in similar high sensitivity and specificity (0.76-0.86). The draft tool showed excellent interrater reliability (intraclass correlation coefficient=.95). CONCLUSIONS:The MSProDiscuss tool differentiated RRMS patients from SPMS patients with high sensitivity and specificity. In clinical practice, it may be a useful tool to evaluate early, subtle signs of MS disease progression indicating the evolution of RRMS to SPMS. MSProDiscuss will help assess the current level of progression in an individual patient and facilitate a more informed physician-patient discussion.

Dataset Information

Plasma proteome in multiple sclerosis disease progression.

Publications

Plasma proteome in multiple sclerosis disease progression.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets